Rapid and selective quantification of sulfite in complex aqueous matrices across a wide concentration range via
Yu Chen1, Waqar Ahmad Qureshi1, Chonghui Yang1
1School of Energy and Power Engineering, Shandong University, Jinan, 250061, China.
Abstract:
Accurate and reliable sulfite detection is essential for ensuring food safety and environmental compliance. Herein, a sulfur dioxide-mediated microwave resonant sensing strategy is employed for sulfite quantification. The approach is based on the chemical conversion of sulfite ions (SO32-) into sulfur dioxide (SO2) gas via acidification, followed by the detection of dielectric changes in the sensing layer induced by gas-phase adsorption. An open split-ring resonator (SRR) based microwave sensor was designed and integrated with two different sensing materials: hydrogen peroxide (H2O2) and a SnO2-polyaniline (SnO2-PANI) composite, to investigate and compare their sensing properties. Electromagnetic field distribution, surface current density, and reflection coefficient (S11) responses were simulated using ANSYS High Frequency Structure Simulator (HFSS). Experimental results reveal that the H2O2-based sensor exhibits an exceptional variation in S11 amplitude with high sensitivity over a sulfite concentration range of 8-320 mg/L, achieving a limit of detection (LOD) of 2.93 mg/L. In contrast, the SnO2-PANI-based sensor demonstrates a strong linear relationship between the frequency shift and sulfite concentration in the range of 8-480 mg/L, with a limit of detection (LOD) of 4.94 mg/L. Multivariate analysis incorporating frequency shift, bandwidth, S11 response, and normalized quality (Q) factor confirms that both sensors effectively capture dielectric constant and loss changes caused by SO2 adsorption. Furthermore, its practical applicability was demonstrated through the determination of target SO32- levels in diverse water samples. Offering rapid response and operational simplicity, this microwave-assisted approach represents a reliable alternative to conventional sulfite detection methods with broad application potential.
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